Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a 'big data compacting and data fusion'-concept to capture diverse adverse ...outcomes on cellular and organismal levels. The approach generates from transcriptomics data set a 'predictive toxicogenomics space' (PTGS) tool composed of 1,331 genes distributed over 14 overlapping cytotoxicity-related gene space components. Involving ∼2.5 × 10
data points and 1,300 compounds to construct and validate the PTGS, the tool serves to: explain dose-dependent cytotoxicity effects, provide a virtual cytotoxicity probability estimate intrinsic to omics data, predict chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperforms and complements existing tests, leading to a hereto-unseen level of DILI prediction accuracy.
Purpose: To identify novel therapeutic opportunities for patients with prostate cancer, we applied high-throughput screening to systematically
explore most currently marketed drugs and drug-like ...molecules for their efficacy against a panel of prostate cancer cells.
Experimental Design: We carried out a high-throughput cell-based screening with proliferation as a primary end-point using a library of 4,910
drug-like small molecule compounds in four prostate cancer (VCaP, LNCaP, DU 145, and PC-3) and two nonmalignant prostate epithelial
cell lines (RWPE-1 and EP156T). The EC 50 values were determined for each cell type to identify cancer selective compounds. The in vivo effect of disulfiram (DSF) was studied in VCaP cell xenografts, and gene microarray and combinatorial studies with copper
or zinc were done in vitro for mechanistic exploration.
Results: Most of the effective compounds, including antineoplastic agents, were nonselective and found to inhibit both cancer and
control cells in equal amounts. In contrast, histone deacetylase inhibitor trichostatin A, thiram, DSF, and monensin were
identified as selective antineoplastic agents that inhibited VCaP and LNCaP cell proliferation at nanomolar concentrations.
DSF reduced tumor growth in vivo , induced metallothionein expression, and reduced DNA replication by downregulating MCM mRNA expression. The effect of DSF
was potentiated by copper in vitro .
Conclusions: We identified three novel cancer-selective growth inhibitory compounds for human prostate cancer cells among marketed drugs.
We then validated DSF as a potential prostate cancer therapeutic agent. These kinds of pharmacologically well-known molecules
can be readily translated to in vivo preclinical studies and clinical trials. (Clin Cancer Res 2009;15(19):6070â8)
Abstract
Increasing amounts of systems toxicology data, including omics results, are becoming publically available and accessible in databases. Data-driven and informatics-tool supported pipeline ...schemas for fitting such data into Adverse Outcome Pathway (AOP) descriptions could potentially aid the development of nonanimal-based hazard and risk assessment methods. We devised a 6-step workflow that integrated diverse types of toxicology data into a novel AOP scheme for pulmonary fibrosis. Mining of literature references and diverse data sources covering previous pathway descriptions and molecular results were coupled in a stepwise manner with informatics tools applications that enabled gene linkage and pathway identification in molecular interaction maps. Ultimately, a network of functional elements coupled 64 pulmonary fibrosis-associated genes into a novel, open-source AOP-linked molecular pathway, now available for commenting and improvements in WikiPathways (WP3624). Applying in silico-based knowledge extraction and modeling, the pipeline enabled screening and fusion of many different complex data types, including the integration of omics results. Overall, the taken, stepwise approach should be generally useful to construct novel AOP descriptions as well as to enrich developing AOP descriptions in progress.
Summary Objectives Targeted therapy against the epidermal growth factor receptor (EGFR) only variably represents a therapeutic advance in head and neck squamous cell carcinoma (HNSCC). This study ...addresses the need of biomarkers of treatment response to the EGFR-targeting antibody cetuximab (Erbitux®). Materials and Methods The intrinsic cetuximab sensitivity of HNSCC cell lines was assessed by a crystal violet assay. Gene copy number analysis of five resistant and five sensitive cell lines was performed using the Affymetrix SNP 6.0 platform. Quantitative real-time PCR was used for verification of selected copy number alterations and assessment of mRNA expression. The functional importance of the findings on the gene and mRNA level was investigated employing siRNA technology. The data was statistically evaluated using Mann–Whitney U-test and Spearman’s correlation test. Results Analysis of the intrinsic cetuximab sensitivity of 32 HNSCC cell lines characterized five and nine lines as cetuximab sensitive or resistant, respectively. Gene copy number analysis of five resistant versus five sensitive cell lines identified 39 amplified protein-coding genes, including YAP1, in the genomic regions 11q22.1 or 5p13-15. Assessment using qPCR verified that YAP1 amplification associated with cetuximab resistance. Amplification of YAP1 correlated to higher mRNA levels, and RNA knockdown resulted in increased cetuximab sensitivity. Assessment of several independent clinical data sets in the public domain confirmed YAP1 amplifications in multiple tumor types including HNSCC, along with highly differential expression in a subset of HNSCC patients. Conclusion Taken together, we provide evidence that YAP1 could represent a novel biomarker gene of cetuximab resistance in HNSCC cell lines.
Nanotechnology is a key enabling technology with billions of euros in global investment from public funding, which include large collaborative projects that have investigated environmental and health ...safety aspects of nanomaterials, but the reuse of accumulated data is clearly lagging behind. Here we summarize challenges and provide recommendations for the efficient reuse of nanosafety data, in line with the recently established FAIR (findable, accessible, interoperable and reusable) guiding principles. We describe the FAIR-aligned Nanosafety Data Interface, with an aggregated findability, accessibility and interoperability across physicochemical, bio-nano interaction, human toxicity, omics, ecotoxicological and exposure data. Overall, we illustrate a much-needed path towards standards for the optimized use of existing data, which avoids duplication of efforts, and provides a multitude of options to promote safe and sustainable nanotechnology.
The Fiber Pathogenicity Paradigm (FPP) establishes connections between fiber structure, durability, and disease‐causing potential observed in materials like asbestos and synthetic fibers. While ...emerging nanofibers are anticipated to exhibit pathogenic traits according to the FPP, their nanoscale diameter limits rigidity, leading to tangling and loss of fiber characteristics. The absence of validated rigidity measurement methods complicates nanofiber toxicity assessment. By comprehensively analyzing 89 transcriptomics and 37 proteomics studies, this study aims to enhance carbon material toxicity understanding and proposes an alternative strategy to assess morphology‐driven toxicity. Carbon materials are categorized as non‐fibrous, high aspect ratio with shorter lengths, tangled, and rigid fibers. Mitsui‐7 serves as a benchmark for pathogenic fibers. The meta‐analysis reveals distinct cellular changes for each category, effectively distinguishing rigid fibers from other carbon materials. Subsequently, a robust random forest model is developed to predict morphology, unveiling the pathogenicity of previously deemed non‐pathogenic NM‐400 due to its secondary structures. This study fills a crucial gap in nanosafety by linking toxicological effects to material morphology, in particular regarding fibers. It demonstrates the significant impact of morphology on toxicological behavior and the necessity of integrating morphological considerations into regulatory frameworks.
Emerging nanofibers, akin to asbestos, hold potential risks, yet their small size impedes rigidity, challenging toxicity evaluation. This meta‐analysis of omics studies discerns varying effects among non‐fibrous, short/high‐ratio, tangled, and rigid carbon fibers, shedding light on toxicity mechanisms and linking fiber‐like harm to material structures. Surprisingly, previously deemed safe NM‐400 exhibits danger due to its distinctive structure.
Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have ...announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high‐throughput and high‐content screening assays, dose‐response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer‐by‐design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation.
Safety assessment of advanced materials, such as nanomaterials, should optimally be inherent to material discovery and technological innovation. The 50 New Approach Methodologies (NAMs) covering eight overlapping conceptual categories are shown to substantially provide added value and decision support to current safety assessment practices by bringing in more data, higher precision, and deeper understanding of toxicity mechanisms.
A paradigm shift is taking place in risk assessment to replace animal models, reduce the number of economic resources, and refine the methodologies to test the growing number of chemicals and ...nanomaterials. Therefore, approaches such as transcriptomics, proteomics, and metabolomics have become valuable tools in toxicological research, and are finding their way into regulatory toxicity. One promising framework to bridge the gap between the molecular-level measurements and risk assessment is the concept of adverse outcome pathways (AOPs). These pathways comprise mechanistic knowledge and connect biological events from a molecular level toward an adverse effect outcome after exposure to a chemical. However, the implementation of omics-based approaches in the AOPs and their acceptance by the risk assessment community is still a challenge. Because the existing modules in the main repository for AOPs, the AOP Knowledge Base (AOP-KB), do not currently allow the integration of omics technologies, additional tools are required for omics-based data analysis and visualization. Here we show how WikiPathways can serve as a supportive tool to make omics data interoperable with the AOP-Wiki, part of the AOP-KB. Manual matching of key events (KEs) indicated that 67% could be linked with molecular pathways. Automatic connection through linkage of identifiers between the databases showed that only 30% of AOP-Wiki chemicals were found on WikiPathways. More loose linkage through gene names in KE and Key Event Relationships descriptions gave an overlap of 70 and 71%, respectively. This shows many opportunities to create more direct connections, for example with extended ontology annotations, improving its interoperability. This interoperability allows the needed integration of omics data linked to the molecular pathways with AOPs. A new AOP Portal on WikiPathways is presented to allow the community of AOP developers to collaborate and populate the molecular pathways that underlie the KEs of AOP-Wiki. We conclude that the integration of WikiPathways and AOP-Wiki will improve risk assessment because omics data will be linked directly to KEs and therefore allow the comprehensive understanding and description of AOPs. To make this assessment reproducible and valid, major changes are needed in both WikiPathways and AOP-Wiki.
The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials ...(ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs.
The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms.
We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the "representational state transfer" (REST) API enables building user friendly interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure-activity relationships for nanomaterials (NanoQSAR).
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